Fixed-Charge Facility Location Problems

Fernández, Elena; Landete, Mercedes

doi:10.1007/978-3-319-13111-5_3

Cited by 12 publications

(13 citation statements)

References 120 publications

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“…The SGEP is two‐fold; it consists of (i) a facility location problem and (ii) a routeing assignment problem. Facility location and routeing assignment problems have been studied extensively for applications in supply chain, emergency, pipeline, and telecommunications networks [2, 3]. We refer to topology (or network) design as the process of placing nodes within a network, and to route design as the process of link assignment and bandwidth allocation between nodes.…”

Section: Related Workmentioning

confidence: 99%

Optimal placement of data concentrators for expansion of the smart grid communications network

et al. 2019

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Evolving power systems with increasing renewables penetration, along with the development of the smart grid, calls for improved communication networks to support these distributed generation sources. Automatic and optimal placement of communication resources within the advanced metering infrastructure is critical to provide a high-performing, reliable, and resilient power system. Three network design formulations based on mixed-integer linear and non-linear programming approaches are proposed to minimise network congestion by optimising residual buffer capacity through the placement of data concentrators and network routeing. Results on a case study show that the proposed models improve network connectivity and robustness, and increase average residual buffer capacity. Maximising average residual capacity alone, however, results in both oversaturated and underutilised nodes, while maximising either minimum residual capacity or total reciprocal residual capacity can yield much-improved network load allocation. Consideration of connection redundancy improves network reliability further by ensuring quality-of-service in the event of an outage. Analysis of multi-period network expansion shows that the models do not deviate significantly from optimal when used progressively (within 5% deviation), and are effective for utility planners to use for smart grid expansion.

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Section: Related Workmentioning

confidence: 99%

Optimal placement of data concentrators for expansion of the smart grid communications network

et al. 2019

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“…Since the SPLP literature is vast, we focus here on papers that present polyhedral results, and refer the reader to [10,12,19,23] for surveys of other approaches. Figure 1: Graph corresponding to a circulant inequality with p = 8 and q = 3.…”

Section: Literature Reviewmentioning

confidence: 99%

“…We call the inequalities (12) augmented HIs. A natural question is to determine conditions for augmented HIs to define facets.…”

Section: Facility Augmentationmentioning

confidence: 99%

“…Balinski [2] showed that the set covering problem can be transformed to the SPLP, which implies that the SPLP is N P-hard in the strong sense. Surveys on theory, algorithms and applications of the SPLP include [10,12,19,23]. The current leading exact algorithms, such as those in [20,21], are capable of solving random planar instances with thousands of facilities and clients to proven optimality.…”

Section: Introductionmentioning

confidence: 99%

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New valid inequalities and facets for the Simple Plant Location Problem

Galli

Letchford

Miller

2018

European Journal of Operational Research

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The Simple Plant Location Problem is a well-known (and N P-hard) combinatorial optimisation problem, with applications in logistics. We present a new family of valid inequalities for the associated family of polyhedra, and show that it contains an exponentially large number of new facet-defining members. We also present a new procedure, called facility augmentation, which enables one to derive even more valid and facet-defining inequalities.

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“…Notably, in such solution approaches in the case of non-degenerated problems, any extreme point would be a local optimal solution. As recent applications of the fixed charge problem containing both concepts of fixed and variable costs were used in the network flow problems by [9] and in the facility location problems by [10] (see also [11,12]). Furthermore, Arora [13] introduced a systematic approach that finds an exact solution for the fixed charge problem.…”

Section: Introductionmentioning

confidence: 99%

An effective solution approach for multi-objective fractional fixed charge problem with fuzzy parameters

2018

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A multi-objective fixed charge problem in existence of several fractional objective functions with triangular fuzzy parameters is considered in this study. The problem previously has been tackled only by Upmanyu and Saxena [1] with a method containing wrong mathematical concepts (see the commentary of Kaur and Kumar [2]). To overcome the shortcomings of the literature, an effective solution approach based on a typical goal programming approach is proposed to solve the problem for obtaining a Paretooptimal solution. The proposed approach considers the shortcomings of the method of Upmanyu and Saxena [1] and applies no ranking function of fuzzy numbers. In addition, the goal programming stage considers no preference from decision maker. The computational experiments provided by an example of the literature, prove the effectiveness of the proposed approach. Conflicts of interest: noneRemainder of the paper is organized by five sections. Section 2, describes some basic definitions and concepts of fuzzy theory and optimization theory. Section 3, introduces the FMFFCP, analyzes its formulation and deals with its non-linearity. Section 4, organizes the goal programming based solution approach proposed for the FMFFCP. Section 6, contains an illustrative numerical example from the literature to analyze the performance of the proposed solution approach provided by Section 4. Finally, the paper is ended by remarking some conclusions in Section 6. Basic conceptsSome basic definitions from fuzzy theory which will be applied later in this paper are explained in this sub-section. fuzzy theory, exact and meta-heuristic solution approaches.

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Fixed-Charge Facility Location Problems

Cited by 12 publications

References 120 publications

Optimal placement of data concentrators for expansion of the smart grid communications network

Optimal placement of data concentrators for expansion of the smart grid communications network

New valid inequalities and facets for the Simple Plant Location Problem

An effective solution approach for multi-objective fractional fixed charge problem with fuzzy parameters

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